DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-19 are pending and under examination.
This application is a CON of US 15/776,967, which was a National Stage application under 35 USC 371, and claims priority to an EP priority document filed 12/3/2015. The effective filing date for the pending claims is 12/3/2015. The Examiner has reviewed the prosecution history.
This application has published as US PG-Pub 2023/0151421 A1.
The petition related to the sequence listing has been granted under separate cover.
The Sequence listing and associated documents filed 2/2/2023 have been entered.
The amendment to the specification related to the sequence listing has been entered.
Two IDS statements have been entered and considered.
The drawings are objected to because the figures are difficult to discern, due to faint lines, small typeface or fuzzy reproduction. Specifically, Figure 1A has element numbers that are faint or blurry, as well as text that is difficult to read. Figure 1B has text in element 118 that is impossible to discern. The details of Figure 1C are unclear in general, particularly elements 123 and 124. Applicant is requested to review all drawings for appropriate legibility. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
The disclosure is objected to because of the following informalities: at page 42, in the section labeled “Example 6.” The formula set forth is not legible. The various subscripts are impossible to discern, even upon enlargement of the text.
Appropriate correction is required.
Claim Objections
Claims 1-19 are objected to because of the following informalities: Overall, a claim should begin with a single capital letter and end with a single period. Claim 1 recites multiple periods in certain substeps, and Claim 1 also set forth capital letters at the beginnings of each substep.
Claim 8 recites “The method of any of claim 5…” which appears to be an editing error. The claim should read “The method of claim 5…”
The recitation of Formula I in claim 16 line 3, and the explanation (lines 4-10) are unclear. When items such as (RSC,SCm) are all together in one item, it is unclear what mathematical operation is being performed. Similarly, in the description of Formula I, items such as “SCmgenome” in line 5 are unclear, and not clearly defined in any previous claim from which it depends (claims 15, and 1). This term is also referred to as “SCm genome” in lines 6 and 7, so it is unclear if the first recitation is a typographical error or a different element or calculation. It is suggested that perhaps a variable should be used for each specific term, specific mathematic operators be set forth, and then each variable be clearly and specifically identified in the claim, such that the mathematical operations intended to be performed by Formula I are clearly identified.
Claim 17 is objected to under 37 CFR 1.75(c) as being in improper form because a multiple dependent claim should refer to other claims in the alternative only. See MPEP § 608.01(n). Accordingly, the claim has not been further treated on the merits. Claim 17 depends from claim 16, and from claim 14.
Claim 19 depends from claim 17 objected to as being improperly multiply dependent above, and cannot be further treated on the merits.
Appropriate correction is required.
Claims 1-16, 18 are under examination.
Claim Interpretation
The claims in this application are given their broadest reasonable interpretation (BRI) using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-16, 18 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of mental steps, mathematic concepts, organizing human activity, or a natural law without significantly more.
Applicant is directed to MPEP 2106 for the most current and complete guidelines in the analysis of patent- eligible subject matter. The current MPEP is the primary source for the USPTO’s patent eligibility guidance.
With respect to step (1): YES, the claims are drawn to statutory categories: processes.
With respect to step (2A) (1): YES, the claims recite an abstract idea, law of nature and/or natural phenomenon. The claims explicitly recite elements that, individually and in combination, constitute one or more judicial exceptions (JE).
Mathematic concepts, Mental Processes or Elements in Addition (EIA) in the claim(s) include:
1. A method for determining the clonality of a Master Cell Bank (MCB), said MCB resulting from predictable or not predictable insertion of a transgene of known sequence into a host progenitor cell (HPC) genome of known sequence, said method comprising the steps of:
(Preamble, indicating a method, and the goal of the method, and defining the MCB.)
a) Identifying one or more transgene insertion regions (TIRs) in the genome of a reference subclone cell (RSC), wherein the RSC has been isolated from the MCB for which clonality is to be determined, and wherein said identifying is achieved by
i. paired-end sequencing of said RSC genome to obtain an RSC genome sequence or RSC genome sequences; and
(EIA- a step of data gathering, by performing the well-known laboratory process of paired-end sequencing. MPEP 2106.05(g).)
ii. alignment of said RSC genome sequence or sequences to said known HPC genome sequence and said known transgene sequence, thereby yielding one or more transgene insertion regions (TIRs);
(Mathematic concept of applying algorithms to the sequence read data, and the reference data, to identify regions of identity and calculate measures of similarity. Specification, p20 “Well-known algorithms for sequence alignments are for instance Needleman-Wunsch algorithm, Smith-Waterman algorithm or Waterman-Eggert algorithm or Burrows-Wheeler transform. Well-known tools for sequence alignments are for instance BLAST, BLAT, WMBOSS, Clustal, BWA, Bowtie.” MPEP 2106.04(a)(2) section I.)
b) Determining one or more TIRs as identified in step (a) with the highest degree of sequence coverage, wherein said sequence coverage refers to the number of times a given nucleic acid sequence containing a given TIR is read during the sequencing process by partially overlapping reads;
wherein said one or more TIRs with the highest degree of sequence coverage are assigned as reference TIRs (RTIRs);
(Mathematic Concept of counting the number of sequence reads aligned to a TIR, and a Mental Process of recognizing the TIR with the highest number of aligned reads, and making a judgement as to whether that TIR should be annotated as a RTIR. MPEP 2106.04(a)(2) sections 1 and 3.)
c) Identifying one or more transgene insertion regions (TIRs) in the respective genomes of one or more subclone (SCs);
wherein each of the SCs has been isolated from the MCB for which clonality is to be determined but is independent of said RSC, wherein said identifying is achieved by
i. paired-end sequencing of each respective SC genome to obtain an SC genome sequence or SC genome sequences; and
(EIA- a step of data gathering, by performing the well-known laboratory process of paired-end sequencing. MPEP 2106.05(g).)
ii. alignment of each respective SC genome sequence or sequences to said known HPC genome sequence and said known transgene sequence, thereby yielding one or more comparative transgene insertion regions (CTIRs);
(Mathematic concept of applying algorithms to the sequence read data, and the reference data, to identify regions of identity and calculate measures of similarity. Specification, p20 “Well-known algorithms for sequence alignments are for instance Needleman-Wunsch algorithm, Smith-Waterman algorithm or Waterman-Eggert algorithm or Burrows-Wheeler transform. Well-known tools for sequence alignments are for instance BLAST, BLAT, WMBOSS, Clustal, BWA, Bowtie.” MPEP 2106.04(a)(2) section I.)
d) Comparing said one or more RTIRs determined in step (b) with the respective CTIRs determined in step (c);
(Mental Process of comparison between two TIR (reference, and cloned), however the basis of comparison is unlimited. MPEP 2106.04(a)(2) Section 3).
e) Evaluating the correspondence between each of said one or more CTIRs present in a respective SC and corresponding RTIRs present in said RSC; and
(Mental process of evaluation, which requires observation, analysis and judgement as to whether the CTIR “corresponds” to a RTIR. The nature or aspect to be evaluated is not specified. MPEP 2106.04(a)(2) section 3.)
f) Determining clonality of said MCB based on said correspondence evaluated in part (e), wherein said MCB is considered to be monoclonal, if said RSC and said one or more SCs are grouped into the same cluster.
(Mental process and Mathematic Concept- Determining clonality is a mental process of observing the results of a mathematic clustering analysis, and making a judgement as to whether the MCB is monoclonal. The clustering analysis required to carry out the determination is a Mathematic Concept of calculating a value describing the relatedness of two or more nucleic acid sequences to one another. (specification p5) MPEP 2106.04(a)(2) sections 1 and 3).
2. The method of claim 1, wherein paired-end sequencing involves sequencing of a given nucleic acid molecule from both ends of said nucleic acid molecule, thereby generating pairs of reads for a given nucleic acid molecule representing a fragment of the genome to be sequenced.
(EIA- data gathering step, describing the paired-end sequencing process. MPEP 2106.05(g)).
3. The method of claim 1, wherein said RSC is sequenced with a higher sequence coverage compared to said one or more SCs.
(EIA- describing the results of the data gathering AND a mathematic concept of one value being higher than another.
4. The method of claim 1, wherein said MCB results from the insertion of said transgene at multiple positions into said HPC genome, wherein said random insertion is preferably effected using a retroviral vector.
(EIA- describing the source cells, related to the data gathering steps. MPEP 2106.05(g).)
5. The method of claim 1, wherein the determination TIRs comprises classification of paired-end read 1 sequences and paired-end read 2 sequences derived from paired-end libraries into 4 classes, wherein (a) class 1 comprises read 1 sequences mapping to said transgene; (b) class 2 comprises read 1 sequences mapping to said HPC genome; (c) class 3 comprises read 2 sequences mapping to said transgene; and (d) class 4 comprises read 2 sequences mapping to said HPC genome; wherein said read 1 and said read 2 represent respective forward and backward reads corresponding to the 5' and 3' ends of a given nucleic acid molecule within a nucleic acid cluster generated in sequencing of a nucleic acid library of said RSC or said one or more SCs.
(Mental Process of observing each read of a pair, and judging where each read should be classified, based on the alignment/ mapping location. MPEP 2106.04(a)(2) section 3.)
6. The method of claim 5, wherein read 1 sequences are combined with the corresponding read 2 sequences using a flow cell sequence identifier, wherein said sequence identifier comprises information of the flow cell lane, the tile number within the flow cell, the "x" coordinate of the nucleic acid cluster within a tile, and the "y" coordinate of the nucleic acid cluster within a tile, thereby assigning each sequence pair corresponding to read 1 and read 2 sequences a unique position within the flow cell.
(EIA- describing data gathered from the sequencing process, related to the flow cell and flow cell processes. MPEP 2106.05(g))
7. The method of claim 5, wherein the respective read 1 and read 2 sequences of a respective read pair are separately aligned to the known sequences of the transgene and the HPC genome.
(Mathematic concept of applying algorithms to the sequence read data, and the reference data, to identify regions of identity and calculate measures of similarity. Specification, p20 “Well-known algorithms for sequence alignments are for instance Needleman-Wunsch algorithm, Smith-Waterman algorithm or Waterman-Eggert algorithm or Burrows-Wheeler transform. Well-known tools for sequence alignments are for instance BLAST, BLAT, WMBOSS, Clustal, BWA, Bowtie.” MPEP 2106.04(a)(2) section I.)
8. The method of any of claim 5, wherein only the read pairs comprising class 1 and 4 sequences and the read pairs comprising class 2 and class 3 sequences are selected for further analysis.
(Mental Process of observation of data, and selection of data meeting a condition. MPEP 2106.04(a)(2) section 3).
9. The method of claim 5, wherein said TIRs are identified by aligning the paired-end read sequences corresponding to class 2 and class 4 to the HPC genome, thereby defining a 2kb region for each of said TIRs in the HPC genome.
(Mathematic concept of applying algorithms to the sequence read data, and the reference data, to identify regions of identity and calculate measures of similarity. Specification, p20 “Well-known algorithms for sequence alignments are for instance Needleman-Wunsch algorithm, Smith-Waterman algorithm or Waterman-Eggert algorithm or Burrows-Wheeler transform. Well-known tools for sequence alignments are for instance BLAST, BLAT, WMBOSS, Clustal, BWA, Bowtie.” MPEP 2106.04(a)(2) section I.)
10. The method of claim 1, comprising determining n RTIRs with the highest sequence coverage in the paired-end NGS library; wherein n is an integer from 5 to 50, preferably 5, 10, 15, 20, 25, 30, 35, 40, 45 or 50.
(Mathematic Concept of counting RTIR with highest coverage. MPEP 2106.04(a)(2) section 1).
11. The method of claim 10, wherein the first n RTIRs with highest sequence coverage are determined based on a) the number of reads of a respective paired-end read sequence corresponding to class 2 and class 4 mapping to the HPC genome, wherein higher number of reads indicates inclusion as an RTIR; and b) the partial overlap of the number of reads of a respective paired-end read sequence corresponding to class 2 and class 4, wherein lower partial overlap of number of reads indicates inclusion as an RTIR.
(Mathematic concept further defining what is to be counted. MPEP 2106.04(a)(2) section 1.)
12. The method of claim 10, wherein each of the first n RTIRs in said RSC genome is compared with the corresponding genomic location of said CTIRs in each of said one or more SC genomes.
(Mental Process of observing the selected RTIR and comparing it to a location in a CTIR, and making a judgement. MPEP 2106.04(a)(2) 3)
13. The method of claim 12, wherein comparison of said RTIRs in said RSC and said CTIRs in said one or more SCs is achieved by generating a presence/absence matrix of insertion regions, wherein one matrix dimension represents said n RTIRs of said transgene in said RSC genome and another, preferably orthogonal, matrix dimension represents said RSC and each of said one or more SCs.
(Mathematic Concept of generating an orthogonal matrix of information. MPEP 2106.04(a)(2) section 1).
14. The method of claim 13, wherein the presence or absence of a respective CTIR in said one or more SCs relative to a respective RTIR in said RSC is represented in the matrix as a binary color code, wherein a first color represents the respective presence or absence of a respective RTIR in said RSC, the respective presence or absence of a respective CTIR in said one or more SCs, and wherein a second color represents the respective absence or presence of a respective RTIR in said RSC, the respective absence or presence of a respective CTIR in said one or more SCs.
(Mathematic concept of representing data in a binary format, where the binary format represents certain information. MPEP 2106.04(a)(2) section 1).
15. The method of claim 1, wherein the relationship between said RSC and each of the said one or more SCs is evaluated by calculation of a distance matrix.
(Mathematic concept of calculating the distances between certain data elements. MPEP 2106.04(a)(2) section 1.)
16. The method of claim 15, wherein the distance matrix is calculated based on the following formula (I),
Dd (RSC,SCm) = 1 – (2 * N(total) / [N(CTIR) + N(RTIR)])
said RSC genome and a respective SCmgenome, wherein N(total) is the number of insertion regions present both in said RSC genome and said SCm genome; N(CTIR) is the total number of insertion regions present in said SCm genome; and N(RTIR) is the total number of insertion regions present in said RSC genome; wherein Dd (RSC,SCm) represents the distance, on a scale of 0 to 1, wherein a distance of 0 represents clonal identity between said RSC and a respective SCm, and 1 represents clonal difference.
(Mathematic concept of calculating a distance value or matrix. MPEP 2106.04(a)(2) section 1.)
17. The method of claim 16, wherein the parameters N(total), N(CTIR) and/or N(RTIR) are calculated based on the presence/absence matrix of insertion regions generated according to claim 14.
(Not Treated)
18. The method of claim 16, wherein the method comprises representing said one or more SCs relative to the RSC on a common distance matrix.
(Mathematic concept, specifying what is to be represented in a distance matrix or calculation. MPEP 2106.04(a)(2) section 1)
19. The method of claim 17, wherein two respective genomes are considered to belong to a common cluster if the distance between them as calculated according to Formula (I) is 0.
(Not Treated)
Natural law embraced by claim(s) 1-16, 18:
Further, the claims encompass a naturally occurring relationship between the presence of certain naturally occurring nucleic acid sequences, and a naturally occurring phenotype of “clonal” or “not clonal” depending on certain comparisons. These are genotype/ phenotype relationships that naturally exist in subcloned cells whether measured or not.
A Master Cell line is being tested for purity. The sample of the Master Cell has been expanded to a series of single cell subclones. Each subcloned cell is tested for the presence or absence of the transgene expected to be present, as the Master Cell line comprises the transgene. This is a genotype / phenotype relationship between the naturally occurring presence of the particular sequence in the subclone and a naturally occurring phenotype of being “clonal” or identical to the Master Cell line, thereby providing a measure of purity or clonality of the Master line.
With respect to step 2A (2): NO, the claims do not integrate the JE into a practical application (MPEP 2106.04(d)):
“Examiners evaluate integration into a practical application by: (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application, using one or more of the considerations introduced in subsection I supra, and discussed in more detail in MPEP §§ 2106.04(d)(1), 2106.04(d)(2), 2106.05(a) through (c) and 2106.05(e) through (h).”
Claim(s) 1-4, 5 recite the additional non-abstract element(s) of data gathering, or a description of the data gathered.
Data gathering steps are not an abstract idea, they are extra-solution activity, as they collect the data necessary to carry out the JE. MPEP 2106.05(g).
The data gathering does not impose any meaningful limitation on the JE, or how the JE is performed. MPEP 2106.05(g).
The data gathering steps constitute a general link to a technological environment: using sequencing data to establish clonality. (MPEP 2106.05(h), citing Mayo, Bilski, electric Power Group, Genetic Techs Ltd v Merial LLC.)
The additional limitation (data gathering) must have more than a nominal or insignificant relationship to the identified judicial exception to provide integration into a practical application. (MPEP 2106.05(g) citing Mayo, PerkinElmer, Inc. v. Interna Ltd, Intellectual Ventures LLC v. Erie Indem. Co., Electric Power Group LLC v. Alstom S.A.).
Dependent claim(s) 3, 5, 7-16, 18 recite(s) an abstract limitation to the JE reciting additional mathematic concepts, or mental processes. Additional abstract limitations cannot provide a practical application of the JE as they are a part of that JE.
In combination, the limitations of data gathering, for the purpose of carrying out the JE, using a general-purpose computer merely provide extra-solution activity, and fail to integrate the JE into a practical application.
With respect to step 2B: NO, the claims do not recite a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05).
“… an "inventive concept" is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim, as a whole, amounts to significantly more than the judicial exception itself. Alice Corp…”
With respect to claim(s) 1-4, 6: The limitation(s) identified above as non-abstract elements (EIA) related to data gathering do not rise to the level of significantly more than the judicial exception.
With respect to carrying out paired-end sequencing, on cells, or subclones:
Sufficool et al (2015, PTO-1449) demonstrates that next generation sequencing techniques are being applied to measure aspects of clonality of T cells subcloned from patients.
Leung et al (2013 PTO-1449) uses paired end sequencing to assess subclones of microbial isolate master cells.
Hiatt (2013; PTO-1449) uses paired end sequencing in a high throughput environment to assess genotypes and gene sequences in cancer related cell lines (grown from single cell subclones), and clinical samples.
Boyd et al (2009-PTO-1449) disclose using paired end sequencing techniques to assess clonality of human lymphocytes in a clinical setting.
Bushman et al. (2005-PTO-1449) utilized paired end sequencing to identify the presence and locations of transgene integrations.
DeVree et al (2014: PTO-1449) use paired end sequencing to determine the presence and location of transgenes in cells with little prior knowledge as to the inserted sequence.
Giordano (2011: PTO-1449) specifically recommends PCR and next generation sequencing to identify clonal cells, following integration of the MGMT-P140K-IRES-EGFP encephalomyelitis virus.
Liang-Chu (2015: PTO-1449) uses paired end sequencing to identify contamination in subclones of various common cell lines, and was able to identify that in two cases, two cell lines thought to be distinct and are distinctly named and cloned, are genetically identical.
These elements meet the BRI of the identified data gathering limitations. As such, the prior art recognizes that this data gathering element is routine, well understood and conventional in the art. MPEP 2106.05(d): “If, however, the additional element (or combination of elements) is no more than well-understood, routine, conventional activities previously known to the industry, which is recited at a high level of generality, then this consideration does not favor eligibility.”
Data gathering steps are not an abstract idea, they are extra-solution activity, as they collect the data necessary to carry out the JE. MPEP 2106.05(g).
The data gathering does not impose any meaningful limitation on the JE, or how the JE is performed. MPEP 2106.05(g).
The additional limitation (data gathering) must have more than a nominal or insignificant relationship to the identified judicial exception to provide an inventive concept. (MPEP 2106.05(g) citing Mayo, PerkinElmer, Inc. v. Interna Ltd, Intellectual Ventures LLC v. Erie Indem. Co., Electric Power Group LLC v. Alstom S.A.)
The data gathering steps constitute a general link to a technological environment: the trait prediction methods are intended to be applied to plant populations. (MPEP 2106.05(h), citing Mayo, Bilski, electric Power Group, Genetic Techs Ltd v Merial LLC.)
Therefore, simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception are insufficient to provide significantly more (as discussed in Alice Corp.,).
Dependent claim(s) 3, 5, 7-16, 18 each recite a limitation requiring additional mathematic concepts or mental processes. Additional abstract limitations cannot provide significantly more than the JE as they are a part of that JE (MPEP 2106.05).
In combination, the data gathering steps providing the information required to be acted upon by the JE, performed in a generic computer or generic computing environment fail to rise to the level of significantly more than that JE. The data gathering steps provide the data for the JE, which is carried out by the general-purpose computers. No non-routine step or element has clearly been identified.
The claims have all been examined to identify the presence of one or more judicial exceptions. Each additional limitation in the claims has been addressed, alone and in combination, to determine whether the additional limitations integrate the judicial exception into a practical application. Each additional limitation in the claims has been addressed, alone and in combination, to determine whether those additional limitations provide an inventive concept which provides significantly more than those exceptions. For these reasons, the claims, when the limitations are considered individually and as a whole, are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-16, 18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The metes and bounds of claim 1 are unclear. The claim fails to clearly point out and distinctly identify the steps and parameters of each alignment step (step a)ii) and step c)ii)) such that one of skill would be apprised as to what applicant intends the alignment to identify. No limitations as to identity, similarity, indels, mismatches, or overlaps are set forth. Merely aligning or mapping the sequence is required, and appears to encompass any level of alignment. This does not seem to be helpful in identifying clonal subclones, as a certain level of dissimilarity would appear to indicate a lack of clonality, and not identity. While claims are read in light of the specification, limitations from the specification cannot be read into the claims.
Further to the alignment steps, the wording “thereby yielding one or more transgene insertion regions” is unclear as to what applicant intends to identify. Merely matching the insertion does not identify flanking regions which mark the insertion region. The claim fails to particularly set forth the steps required to identify the relevant information about the transgene alignment to actually identify where the transgene has been inserted in a genome. Aligning the genome against multiple sets of genomic data (HPC, Reference, and transgene) would appear to require specific steps relating to the order of steps and the actual alignment processes performed to achieve the desired results. While claims are read in light of the specification, limitations from the specification cannot be read into the claims.
Further in claim 1, step d, the claim fails to clearly point out and distinctly claim the nature of the comparison between the RTIR and the CTIR sequence data, which would be useful in any later step. What aspect of the two sequences is being compared- length, sequence, methylation sites… sequences have a multitude of possible comparative parameters.
Similarly in step e) of claim 1, the claim fails to clearly point out and distinctly claim the nature of the evaluation of the correspondence between the CTIR and the RTIR. The claim does not identify when a suitable correspondence is identified, how the correspondence is to be evaluated, or when a correspondence is unsuitable. Without such information it is entirely unclear how step f) of claim 1 is to be determined with any statistical certainty.
Further in claim 1, step f) it is entirely unclear what “cluster” any SC is to be grouped in. No clustering steps are set forth in any other limitation, nor is the basis of any clustering made clear. The type of cluster analysis, and the parameter or aspect of the analysis are both lacking, making it impossible to determine clonality on any basis. Further it is unclear what other information or steps are required, when the step reads: “based on”. While claims are read in light of the specification, limitations from the specification cannot be read into the claims.
A broad range or limitation together with a narrow range or limitation that falls within the broad range or limitation (in the same claim) may be considered indefinite if the resulting claim does not clearly set forth the metes and bounds of the patent protection desired. See MPEP § 2173.05(c). In the present instance, claim 23 recites the broad recitation “insertion”, and the claim also recites “preferably effected using a retroviral vector” which is the narrower statement of the range/limitation. . The claim(s) are considered indefinite because there is a question or doubt as to whether the feature introduced by such narrower language is (a) merely exemplary of the remainder of the claim, and therefore not required, or (b) a required feature of the claims.
In claim 5 it is unclear if the limitation is to address step b) or claim 1, as it does not clearly identify where in claim 1 the classification is to take place. It is further unclear in the “wherein” clause, where a “nucleic acid cluster” is obtained, and how the clustering is performed in the method of claim 1. Merely sequencing libraries does not automatically generate nucleic acid clusters: some sort of statistical step is required.
The metes and bounds of claim 6 are unclear, as no previous claim sets forth any structure for performing any step, such as a flow cell. The sequencing steps in claim 1 and/or 5 are not performed in a flow cell. Therefore, the labeling does not necessarily make sense for any further step. It is further unclear how to assign an actual sequencing reaction in a flow cell to a representation of data. The “x” and “y” information appear to refer to an information grid, which does not comprise any elements for binding or storing actual nucleotide reactions.
The metes and bounds of claims 7, 9 are unclear. The claim fails to clearly point out and distinctly identify the steps and parameters of each alignment step such that one of skill would be apprised as to what applicant intends the alignment to identify. No limitations as to identity, similarity, indels, mismatches, or overlaps are set forth. Merely aligning or mapping the sequence is required, and appears to encompass any level of alignment. This does not seem to be helpful in identifying clonal subclones, as a certain level of dissimilarity would appear to indicate a lack of clonality, and not identity. Further to the alignment steps, it is unclear as to what applicant intends to identify. Merely matching the insertion does not identify flanking regions which mark the insertion region. The claim fails to particularly set forth the steps required to identify the relevant information about the transgene alignment to actually identify where the transgene has been inserted in a genome. Aligning the genome against multiple sets of genomic data (HPC, Reference, and transgene) would appear to require specific steps relating to the order of steps and the actual alignment parameters and processes performed to achieve the desired results. While claims are read in light of the specification, limitations from the specification cannot be read into the claims.
In claim 11 step a), the claim fails to clearly point out and distinctly claim the nature of the evaluation of the correspondence between the HPC and the RTIR. Merely mapping the sequence is required, and appears to encompass any level of alignment. The claim does not identify when a suitable correspondence is identified, how the correspondence is to be evaluated, or when a correspondence is unsuitable. Without such information it is entirely unclear how any ultimate clonality is to be determined with any statistical certainty.
In claim 11 step b), the claim fails to clearly point out and distinctly claim the nature of the evaluation of the “partial overlap” of the number of reads. Overlap is generally a term for partially matching sequences at the end of one fragment, while it is used here as “the partial overlap of the number of reads.” It is unclear how the number of reads overlap or how to identify a partial overlap such that the “lower partial overlap of number of reads” makes sense in the determination of clonality. The claim does not identify when a suitable correspondence is identified, how the correspondence is to be evaluated, or when a correspondence is unsuitable. Without such information it is entirely unclear how any ultimate clonality is to be determined with any statistical certainty.
The metes and bounds of claim 12 are unclear. The claim fails to particularly set forth the steps required to identify the relevant information about the transgene alignment to actually identify where the transgene has been inserted in a genome in any of the cell line samples (HPC, MCB, RSC or SC). Aligning the genome against multiple sets of genomic data (HPC, Reference, and transgene) to identify location, as opposed to sequence identity, or in combination with sequence identity, would appear to require specific steps relating to the order of steps and the actual alignment parameters and location identification processes performed to achieve the desired results. While claims are read in light of the specification, limitations from the specification cannot be read into the claims.
The metes and bounds of claim 13 are unclear, as the steps of generating a data matrix representing insertion regions fails to actually identify a genomic location, absent other information. No locations of the RTIR are clearly obtained such that any data matrix would identify any genomic location with any statistical certainty.
A broad range or limitation together with a narrow range or limitation that falls within the broad range or limitation (in the same claim) may be considered indefinite if the resulting claim does not clearly set forth the metes and bounds of the patent protection desired. See MPEP § 2173.05(c). In the present instance, claim 13 recites the broad recitation “one matrix dimension and another matrix dimension”, and the claim also recites “preferably orthogonal” which is the narrower statement of the range/limitation. . The claim(s) are considered indefinite because there is a question or doubt as to whether the feature introduced by such narrower language is (a) merely exemplary of the remainder of the claim, and therefore not required, or (b) a required feature of the claims.
The metes and bounds of claim 15 are unclear. It is unclear what aspect of the “relationship between said RSC and each of said one or more SC is evaluated” by the calculation of a distance matrix. No clear relationship having a specific value, or number, or tally is clearly set forth such that the generic calculation of distance matrices makes sense. One of skill would not necessarily be apprised as to what steps are actually to be performed to achieve the desired results, and the ultimate result of a determination of clonality.
The metes and bounds of claim 16 and claim 18 are entirely unclear, as to the nature of formula I and each element therein. As set forth in the objection to the claims, the nature of each variable, mathematic operation, and result should clearly be set forth in the claim. It is further unclear how any information obtained from any previous claim is to be applied such that the required determination of clonality is ultimately obtained with any statistical certainty.
It is generally suggested that the claims be pared down to include clearly identifiable variables, clearly identifiable statistical calculations or alignment or mapping operations, clearly identify how each result is obtained and then applied to further steps without unneeded repetitive clauses or confusing terms. For example, in claim 24: “wherein paired-end sequencing involves sequencing of a given nucleic acid molecule from both ends of said nucleic acid molecule thereby generating pairs of reads for a given nucleic acid molecule representing a fragment of the genome to be sequenced” could be pared down to something like: “wherein paired-end sequences comprises sequencing a nucleic acid molecule from both ends, generating pairs of reads representing a fragment of the genome to be sequenced.” Such cleaner, more direct phrasing would be most helpful throughout.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-3, 5, 7-9 is/are rejected under 35 U.S.C. 102a1 as being anticipated by Torres (2014; of record in parent).
Torres, R. et al. Engineering human tumor-associated chromosomal translocations with the RNA-guided CRISPR-Cas9 system. Nature Communications (2014) 5:3964.
Claim 1 is drawn to a method of determining the clonality of a master cell line or master cell bank. This is achieved through generating subclone lines, and then sequencing the reference cell line, and each subclone line for the transgene sequence and/or location. Claim 1 “evaluates” the correspondence of the subclones to the reference clone to “determine” clonality of the master cell line if the reference cell line and the subclone line are “grouped into the same cluster.”
Torres provides generating human cell lines in vitro which comprise insertions regions (Abstract). These cell lines were generated according to the results section, p2-3. Torres notes that the ultimate cell lines were mixed clones, derived from plating 2-10 transfected cells. Torres tests each subclone by PCR, by sequence analysis compared to both cells positively harboring the insertion, and cells without the insertion (untransfected). Torres notes: “a DNA library for multiplexed paired-end sequencing was obtained, and deep sequencing analysis of DNA breakpoint regions revealed robust fidelity of CRISPR/Cas9 DSB generation.” (p3) Torres repeated the experiment with human mesenchymal stem cells, E1F2-293A cells, HEK293 cells with each set of subcloned cell lines were compared against initial cell lines with or without the transgene. Torres was able to identify whether a subclone line was “clonal” or representative of the original cell line of interest in several instances. Sequencing, alignment and mapping were carried out as set forth in the results, and in the methods section: library preparation, sequencing and primary data processing. As such this meets the limitations of claim 1.
With respect to claim 2, Torres performs paired end sequencing at page 3.
With respect to claim 3, coverage is addressed in the methods section and supplemental information.
With respect to claim 5, 7-9, Figure 1 shows separating of reads of paired end sequencing as to where they map, and the legend discusses how each read represents parts of the transgene, the genome, or the reference. See also supplemental information.
Claim(s) 1-5, 7-12 and 15 is/are rejected under 35 U.S.C. 102a as being anticipated by Cattoglio (2010).
Cattoglio et al. High-Definition Mapping of Retroviral Integration Sites Defines the Fate of Allogeneic T Cells After Donor Lymphocyte Infusion. (2010) PLOS One 5:12 e15688 and some supplemental information.
Cattoglio is interested in MLV vectors, used in generating T cells for treatment against lymphoma. MLV is a retrovirus. Cattoglio notes that integration of MLV and MLV derived vectors is non-random, with specific preferences for promoters and regulatory regions of active genes. Cattoglio uses LAM-PCR and sequencing to build a genome wide high-definition map of integrations sites of the SFCMM retroviral vector in the genome of peripheral blood T cells from two different donors. Genetic and epigenetic features of each are compared to a non-transformed T cell line genome. MLV integrations cluster within chromatin regions bearing cell-specific epigenetic marks associated with active promoters and regulatory elements.
With respect to claim 1, transduced T cells retrieved from two patients TK38 and TK 48, were selected and expanded. Paired end sequencing of DNA extracted from the transduced cells was performed, and the fragments were sequenced. (SRA026258). Valid sequences were aligned and then mapped to human genome sequence hg18 (reference), the inserted transgene, and initially transduced T cells from the patient. (unique insertion sites from pre-and post-infusion T cells, Table 1, p2). Alignment of inserted genomes and original genomes was compared. The correspondence of subclone inserted sequences to each other, and reference sequences was determined. The “clonality” or a measurement of how close the integrated genome sequence reads are the original sequence of the virus, was determined through bioinformatic pipeline analysis.
With respect to claim 2, Cattoglio sequences both directions, providing paired reads at page 3.
With respect to claim 3 and 10, coverage is addressed in the methods section p12 and supplemental information.
With respect to claim 4, the MLV vector is a retroviral vector.
With respect to claim 5, 7-9, the materials and methods section p12, and Figure S1 shows separating of reads of paired end sequencing as to where they map, and the legend discusses how each read represents parts of the viral insertion, the genome, or the reference. See also supplemental information. Figure S1 discusses clustering.
With respect to claims 11, 12 and 15 Cattoglio counts reads mapping to progenitor genome cells, transformed cells pre-infusion, and viral genome sequences, as well as reads overlapping genomic sequences. Distance matrices for the nucleic acid clustering is performed. S1, materials and methods.
Claim(s) s 1-5, 7-12, 14-16, 18is/are rejected under 35 U.S.C. 102a1 as being anticipated by Gabriel et al.
Gabriel et al. Comprehensive genomic access to vector integration in clinical gene therapy (2009) Nature Medicine 15: 1431-1436.
Gabriel provides both experimental and bioinformatic steps to identify vector integration sites in cell lines, then determining clonality by sequence analysis. The viruses are lentiviruses and retroviruses. Gabriel provides an expanded annotated “analyzable genome” for use in the bioinformatic comparisons.
With respect to claim 1, cells from preclinical and clinical retroviral and lentiviral LAM-PCR experiments were subjected to nested paired end PCR and sequencing. Figure 3, Figure 4. nrLAM-PCR identified more insertion sites, more accurately than LM-PCR. The procedure allowed for quantitative measurement of individual gene-modified clones by scoring of sequence read numbers. Online methods discloses the methods, wherein paired end sequencing is performed, followed by aligning the sequence reads to the appropriate genome (host, virus, reference). Unambiguous mapping of reads was estimated. This determination can be used to determine “clonality” or how similar an insertion sequence or location is to a reference. One cell sample is shown to be monoclonal as 98% of the insertions locate to one gene. (Supplemental Table 4).
With respect to claim 2, Gabriel sequences both directions, providing paired reads at online methods.
With respect to claim 3 and 10 coverage is addressed in the methods section p7 and supplemental information.
With respect to claim 4, the vectors are retroviral vectors.
With respect to claim 5, 7-9, the materials and methods section 7, and Figure 4 shows separating of reads of paired end sequencing as to where they map, and the legend discusses how each read represents parts of the viral insertion, the genome, or the reference. See also supplemental information for monoclonal identification of a sample, compared to the native or pretransfusion sequences. Clustering of sequences is addressed in the creation of the accessible genome and model validation, p1431-1434.
With respect to claims 11-12, 15-16, 18 Gabriel counts reads mapping to progenitor genome cells, transformed cells pre-infusion, and viral genome sequences, as well as reads overlapping genomic sequences. Distance matrices for the nucleic acid clustering is performed (methods, l7 Experimental validation). P 1434, “scientific and clinical relevance of nrLAM-PCR”.
Claim(s) 1-3, 5-13, 15is/are rejected under 35 U.S.C. 102a1 as being anticipated by Sufficool et al.
Sufficool et al. T-cell-clonality assessment by next-generation sequencing improves detection sensitivity in mycosis fungoides. (August 2015) J Am Acad Dermatology. 73:2 p298.
With respect to claim 1, Sufficool tests TCR clones from naïve, rearranged, and cell samples from patients. The rearrangement site, which is approximately the same as a transgene, in that the sequence is not present in naïve cells, undergoes paired end sequencing, alignment to both host, and known pathologic sequences. Evaluating the alignment and mapping of the rearrangements is performed to determine a measurement of clonality of cells. (Figure 2).
With respect to claim 2, Sufficool sequences both directions, providing paired reads at online methods.
With respect to claim 3 and 10, coverage is addressed in the methods section p230-231 and supplemental information.
With respect to claim 5 and 7-9, the materials and methods section, Figure 2-3 shows separating of reads of paired end sequencing as to where they map, and the legend discusses how each read represents parts of the rearrangement, the genome, or the reference. Clustering of sequences is addressed in the methods section and legends.
With respect to claim 6, 13 the miSeq is a flow cell process, and the miSeq reads provide flow cell lane, and x, y coordinates, as well as visual representations. (Fig 2, “miSeq sequencing”.)
With respect to claims 11-12, 15 Sufficool counts reads mapping to un-rearranged genome cells, rearranged sequences, and expected VDJ sequences, as well as reads overlapping genomic sequences. Distance matrices for the nucleic acid clustering is performed (methods, results).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Frye et al. (2016) Industry view on the relative importance of “clonality” of biopharmaceutical-producing cell lines. Biologicals, vol 44, p117-122.
Kaas et al. (2015) Deep sequencing reveals different compositions of mRNA transcribed from the F8 gene in a panel of FVIII-producing CHO cell lines. Biotechnology Journal, v10, p1082-1089.
Peterson et al. (2015) Enhancing cancer cell clonality analysis with integrative genomics. BMC Bioinformatics, vol 16, Suppl 13, Article S7, 17 pages.
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